Vol.:(0123456789) 1 3 Model. Earth Syst. Environ. (2017) 3:28 DOI 10.1007/s40808-017-0296-x ORIGINAL ARTICLE Geospatial modelling for optimum management of fertilizer application and environment protection Javad Seyedmohammadi 1  · Leila Esmaeelnejad 2  · Hassan Ramezanpour 3   Received: 6 January 2017 / Accepted: 9 February 2017 © Springer International Publishing Switzerland 2017 could successfully interpolate soil variables. Thus, the krig- ing geostatistical method used on a large scale could accu- rately evaluate the spatial variability of soil nutrient prop- erties. With regard to soil nitrogen and phosphorus maps, application of more amounts of nitrate and phosphorus fer- tilizers than their optimum level cause ground waters pol- lution and environment damages therefore their application must be carried out with high consideration. Potash fertiliz- ers consumption in land with high CEC results its fxation, too. Precise attention to CEC map and on-time fertilizer application can solve this problem. Therefore, accurate notice to diferent amounts of these parameters in predic- tion maps, critical and optimum levels can well manage fertilizers application, prevents additional costs to farmer, pollution of ground waters and environment resources. Keywords CEC · Kriging · Nitrogen · Paddy soil · Phosphorus · Potassium Introduction Excessive application of nutrient chemical fertilizers such as nitrogen and phosphorus in high agricultural produc- tion and their loadings to aquatic environments are increas- ing concern globally for managing ecosystems, drinking water supply and food production. There are often multiple sources of these nutrients in the landscape, and the difer- ent hydrological fow patterns within stream or river catch- ments, lagoons and seas coastal have considerable infu- ence on nutrient transport, transformation and retention processes that all eventually afect loadings to vulnerable aquatic environments (Hashemi et al. 2016; Firmansyah et al. 2017). Therefore, knowledge of spatial distribution and accurate mapping of soil nutrient properties at diferent Abstract Soil as an important source, guaranties the plant growth and supplies more than 97% of food need of world. Knowledge of soil spatial variability is important in natural and environment resource management, interpolation and soil sampling design, but requires a considerable amount of geo-referenced data. Soil cation exchange capacity (CEC) is a vital indicator of soil fertility quality and pollutant sequestration capacity. Plants such as rice need to provide their nutrient elements by using fertilizers for much more production in surface unit. For this purpose, it is essential to recognize macro-elements amount in soils and prepare their ideal maps. 247 soil samples were collected from depth 0–30 cm with distance minimum 250 m and maxi- mum 1500 m using a stratifed random sampling scheme on central areas of Guilan province located in north of Iran. CEC, total nitrogen, available potassium and phosphorus maps prepared using kriging geostatistical method. Evalu- ation criteria values of root mean square error (RMSE) and mean absolute error (MAE) derived for potassium 27.84 and 0.106, phosphorus 8.17 and 4.63, total nitrogen 0.059 and 0.025 and CEC 4.06 and 3.09, respectively. Criteria value of RMSE and MAE showed that accuracy of pre- pared maps was ideal. The ft of the experimental semi- variograms to the theoretical models indicated that kriging * Javad Seyedmohammadi seyedmohammadi.javad@gmail.com 1 Department of Soil Science, Faculty of Agriculture, University of Tabriz, Tabriz, Iran 2 Department of Soil Science, Faculty of Agricultural Engineering and Technology, College of Agriculture and Natural Resources, University of Tehran, Karaj, Iran 3 Department of Soil Science, Faculty of Agriculture, University of Guilan, Rasht, Iran